Desktop Survival Guide
by Graham Williams


A good introduction is available from

Bagging is bootstrap aggregation. The underlying idea is that part of the error due to variance in building a model comes from the specific choice of the training dataset. So create many similar training data sets, and for each of them train a new function. The final function will then be the average of each functions output.

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